ORIGINAL ARTICLE Modeling Earth Systems and Environment https://doi.org/10.1007/s40808-023-01814-2 Introduction Urban transformation refers to the process of a rural area evolving and developing into an urban landscape through rapid changes and development (Gaubatz 1999; Ma 2002; Bharath et al. 2017; Kumar et al. 2019). During this trans- formation, the natural landscape undergoes signifcant alterations as human activities shape and modify it to accommodate urbanization (Liu et al. 2010; Montgomery et al. 2013). As rural areas transition into urban environ- ments, several notable changes occur. The physical environ- ment becomes increasingly characterized by anthropogenic structures and features created by human beings (Minocha  Sanjit Sarkar sanjitiips@gmail.com Harekrishna Manna harekrishnamanna@gmail.com Moslem Hossain moslemgeo@gmail.com Mriganka Dolui mriganka.dolui@gmail.com 1 Department of Geography, School of Earth Sciences, Central University of Karnataka, Kalaburagi, Karnataka 585367, India 2 Department of Geography, Central University of Karnataka, Kadaganchi, Karnataka 585311, India Abstract The spatio-temporal dynamics and regional land use driving factors are fundamental considerations in achieving suitable and sustainable urban development. These aspects play a signifcant role in shaping cities’ physical, social, and environ- mental dimensions. This article aims to document and analyze the detection of LULC changes and their concentration, along with urban sprawl and prediction for the future. The study utilized multi-temporal satellite imageries of 2001, 2011, and 2021 to analyze the historical land cover, urban expansion, land transformation, growth direction, and urban sprawl in the study area. Subsequently, to predict and simulate future land use/land cover scenarios, the study employed an inte- grated cellular automata (CA)–Markov model using the theTerrSet software. The change detection results revealed that the built-up area had drastically increased from 17.90 to 40.64% from 2001 to 2021, and the barren land and agricultural land had signifcantly decreased. The transition matrix shows that the maximum barren land was converted into a built-up area and fallow land; at the same time, agriculture lost its maximum area, and built-up gained maximum area. The pre- dicted LULC map of 2031 indicates specifc patterns of change, including converting barren land into built-up areas and expanding vegetation cover due to reforestation and agricultural activities. The built-up area is projected to experience a signifcant increase and is estimated to expand by 62.29 km2, representing 50.46% of the total land-use area. Further, the study predicts a decrease in barren land over the ten years; the estimated change in barren land is 14.33%. The fndings demonstrate that the model performed well in projecting the LULC of 2021, achieving an AUC (Area Under the Curve) of 78%. Additionally, the kappa coefcient of 0.8 further supports the model’s capability as a feasible representation of the study area. The study’s fndings contribute to understanding LULC dynamics, urban sprawl, and future projections, and it provides crucial data for planning and decision-making processes, supporting sustainable land use management and informing strategies for suitable urban development in the study area. Keywords Urban dynamics · Urban sprawling · Prediction · Markov model · Kalaburagi · India Received: 17 April 2023 / Accepted: 11 June 2023 © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023 Modeling and predicting spatio-temporal land use land cover changes and urban sprawling in Kalaburagi City Corporation, Karnataka, India: a geospatial analysis Harekrishna Manna 1  · Sanjit Sarkar 1  · Moslem Hossain 2  · Mriganka Dolui 2 1 3